With large investment in warehousing and transport infrastructures, equipment and employees, logistics becomes a worldwide booming industry. Empty backhaul trip and low ELR are problems involved in very complex decision-making processes due to matching vehicles and goods, and dispatching vehicles for goods. The development of public logistics and transport service information systems that provide dynamic and real-time information on vehicles and goods is a base of the proposed DSS. The reduction of ELR contributes to minimizing the logistics cost, energy and pollution. Developing a framework of the proposed DSS for PLISMO, and related matching and stowage scheduling models, the proposed method is promising to provide the meaningful insights and quantitative advices on how to build a DSS for PLISMO by using optimization models and advanced information technologies. As a result, the contribution of the proposed DSS would be enormous.